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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Geothermal Direct-Use Applications for the District Energy System in Bucharest, Romania

The city of Bucharest, Romania, hosts the second-largest district energy system (DES) in the world. Geothermal resources can be considered as a supplementary heat source to support the demand for domestic hot water and space heating in the winter and shoulder seasons. The National Laboratory of the Rockies (NLR) has conducted a study that considers geothermal energy to serve a fraction of the existing district heating network operated by Electrocentrale Bucure?ti (ELCEN), the utility operating the DES. Lower Cretaceous and Jurassic limestones make up the main geothermal aquifer underlying Bucharest, which hosts temperatures suitable for district heating (up to 90 degrees C to the north of the city). Anomalous geothermal gradients have been observed to the north of the city, where a pumped well has produced 82 degrees C brine at the wellhead to feed the Therme Bucharest Spa. An anomalous gradient has also been reported to the southeast of the city (35 degrees C/km). NLR modeled the building heating loads of a small portion of the DES (a block of nine prototypical buildings) in its Urban Renewable Building and Neighborhood Optimization (URBANopt ) platform. To simulate meeting a baseload benchmark of 20 MWth deliverable to a small portion of the DES, the NLR team used GEOPHIRES to model production scenarios for (1) hydrothermal systems coupled with heat pumps targeting the main geothermal aquifer in the north, (2) enhanced geothermal systems targeting hot dry rock in the southeast, and (3) huff-and-puff systems targeting a gradient of 25 degrees C/km. Finally, NLR conducted a high-level sensitivity study around the techno-economics of these systems. The outcomes of this work indicate that hot dry rock geothermal resources that can deliver at least 90 degrees C hot water to the Geothermal District Energy System (GeoDES) offer a possible solution for supplemental geothermal heat delivered to the existing DES.

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

Design and optimization of higher order mode couplers for the superconducting cavities of the PERLE energy recovery linac

The Powerful Energy Recovery Linac for Experiments (PERLE) is an energy recovery linac (ERL) facility based on superconducting radio-frequency (SRF) technology to be hosted at the Laboratoire de Physique des 2 Infinis Irène Joliot-Curie (IJCLab) in France. With a target beam power of 10 MW, PERLE aims to demonstrate the high-current, continuous wave, multi-pass operation to validate options for future high-energy machines, such as the 50 GeV ERL proposed for the Large Hadron electron Collider (LHeC) and the Future Circular electron-hadron Collider (FCC-eh), and host dedicated particle physics and nuclear experiments. In high-current ERLs, the regenerative Beam Breakup (BBU), emerging from the beam and cavity Higher Order Modes (HOMs) interaction, is a major concern for their stable operation. Beam-induced HOMs can increase the cavity heat load at cryogenic temperature and cause beam instabilities. HOM couplers are installed in the cavity beam pipes to absorb HOM energy and mitigate these effects. This thesis presents the design and optimization of several coaxial HOM couplers for the 5-cell 801.58 MHz elliptical Nb cavities of the 500 MeV PERLE ERL configuration. The RF transmission of the HOM couplers was optimized to enhance the damping of the most dangerous HOMs. The optimized HOM couplers were integrated into endgroups to simulate their damping performance and thermal behavior. The optimized HOM couplers were 3D-printed in epoxy and copper-coated. Low-power RF measurements were conducted on the produced HOM couplers installed in copper PERLE-type cavities to validate their damping performance and propose several endgroups for the PERLE 5-cell cavity to mitigate HOMs below the BBU instability limits.

Barbagallo, Carmelo↗
DOE OSTI2026

Design and Modeling of the Charge Readout of a SiMOS Quantum Dot with a Single Electron Transistor and CryoCMOS

Single electron spin qubits trapped in SiMOS quantum dots are a promising technology for scaling to thousand- or million-qubit systems due to their compatibility with mature CMOS manufacturing processes. A readout system that combines a single electron transistor with a custom cryogenic CMOS amplification and digitization chain offers key advantages by avoiding the use of bulky RF components or room-temperature interconnects. We present design techniques and simulation results for an optimized qubit-SET cryoCMOS interface, culminating in the design of the QNDR1 ASIC, the first cryogenic readout ASIC designed under the Quandarum project, which targets the development of a many-channel spin qubit based detector for use in high energy physics.

Quinn, Adam [Fermilab] (ORCID:0009000605056371)↗
DOE OSTI2024

E3SM: Improved Climate Prediction with Exascale Capability

The Energy Exascale Earth System Model (E3SM) project is an ongoing, state-of-the-science earth system modeling, simulation, and prediction effort that optimizes Department of Energy (DOE) computing resources to meet the science needs of the nation and the agency’s mission objectives. Climate simulation has become a proven tool for identifying and quantifying the impacts of climate change, but even greater accuracy is required at all levels to improve forecast precision. Understanding the impact of climate change on global and regional water cycles is one of the highest priorities and most difficult challenges in climate change prediction. As part of a subproject of DOE’s Exascale Computing Project, a multidisciplinary team including geophysical and computational scientists developed a multiscale modeling framework (MMF) to refine cloud representation in E3SM climate simulation on GPU accelerated supercomputers, making higher resolution, more computationally efficient predictions possible.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Optimizing Heat Recovery with Storage: Control Validation and Sensitivity Analysis of the Time-Independent Energy Recovery Plant Using Modelica

Heat recovery in large building central plants saves energy but traditionally requires simultaneous heating and cooling. The Time-Independent Energy Recovery (TIER) plant shifts this paradigm by integrating thermal energy storage (TES) to enable heat recovery regardless of concurrent demand, offering a highly efficient, space-saving solution to achieve California’s energy goals. However, its integration of heat recovery chillers, cooling-only chillers, cooling towers, and trim air-source heat pumps (ASHPs) creates growing control and sizing complexity. To overcome this, this study employs high-fidelity Modelica dynamic simulation to validate TIER control sequences and optimize equipment sizing. We translated the written Sequences of Operation into executable Control Description Language (CDL) to test logic against sub-hourly loads. This verification workflow successfully identified and resolved critical vulnerabilities, such as thermal storage freezing and equipment short-cycling, in a virtual environment prior to physical deployment. Then, the study analyzes TIER plant performance across three simulated building types in three locations, and a real building load profile, ensuring variety in heating and cooling loads, and simultaneity factors and explores sizing rules for the TES and ASHP capacity. The analysis shows that the TIER plant operates equipment efficiently leading to a plant SCOP of around 7.5 across all scenarios, higher than a traditional ASHP plant, and a viable pathway to de-risk complex system design and control through simulation to identify optimal designs that maximize energy efficiency, minimize operational costs, and ensure robust operation in varied environmental conditions, thereby facilitating the broader adoption of such a solution for large buildings.

Zanetti, Ettore↗
DOE OSTI2025

O4855---Geometry_Optimizer_with_NSGA-II

It is a geometry optimizer, written for MCNP geometries but also applicable to other simulation programs. It uses NSGA-II optimization algorithm to change the specified input parameters to iteratively improve the requested tally values over generations.

Erdem, Omer↗
DOE OSTI2025

ELM model simulations of Plum Island Ecosystems LTER low marsh site 2018-2020

Model simulations using the Department of Energy's Energy Exascale Earth System Model (E3SM) land model (ELM) with improved capabilities to represent vegetation response to salinity and inundation. The simulations were conducted for a tidal salt marsh at Plum Island Ecosystems Long Term Ecological Research (LTER) site near Rowley, Massachusetts, USA; the site is a low marsh dominated by Spartina alterniflora. The model was forced with site-specific meteorology, salinity and tidal cycles from 2018-2020. Four sets of model simulations are included and described below:1. Parameterization of the salinity response function. These simulations tested different combinations of values for optimal salinity and salinity tolerance.2. Model evaluation. This comparison conducted simulations using the default model, the salinity function only, the submergence function only, and both the salinity and submergence functions. 3. Salinity scenarios. These simulations used the 2018 salinity input data varied by -5 to +10 ppt salinity.4. Water level scenarios. These simulations used the tide height varied by -10 to +50 cm. These simulations were used to demonstrate how the salinity and submergence functions better represent carbon uptake by tidal salt marshes.The data package includes netCDF files used as forcing files for tide height and salinity, one for each year 2018-2020 at observed salinity concentrations, and an additional three forcing files in which salinity concentrations were varied 5 ppt lower, 5 ppt higher, and 10 ppt higher than the measured 2018 time series. Also included are python scripts for creating forcing files, plain text parameter and command files for running simulations, model outputs in netCDF format, and python scripts for visualizing outputs. Code for the modified E3SM model is archived in Sulman et al 2023 at doi:10.15485/1991625. More detail about files is provided in the README.md file.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Roadrunner

SAND2026-17073O Roadrunner software provides a comprehensive platform for simulating the mechanical behavior of crystalline materials under various loading conditions, allowing users to investigate the effects of dislocation slip hardening and damage evolution. Developed as a fork of the Multiphysics Object Oriented Simulation Environment (MOOSE) software from Idaho National Laboratory, Roadrunner is optimized for high-performance computing and can simulate large-scale problems, enabling researchers to explore complex scenarios. Its applications include material design and optimization in aerospace and automotive industries, investigation of failure mechanisms in structural materials, and development of predictive models for crystalline materials under various loading conditions. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Lim, Hojun [Sandia National Lab. (SNL-CA), Livermo↗
DOE OSTI2025

Inertial Confinement Fusion Design Search Using Bayesian Optimization

Inertial confinement fusion (ICF) experiments rely on complex multi-physics simulation codes such as the Lawrence Livermore National Laboratory-developed HYDRA to guide design work. However, these simulations have several dozen tunable parameters and can be computationally expensive. This makes searching the parameter space challenging and time-consuming. Recently developed automated tools utilize Bayesian optimization to search these high-dimensional parameter spaces for optimal designs. The optimization tools run 2D integrated simulations in HYDRA to converge on a design that produces specified scalar or vector outputs. In this paper, we apply the Bayesian optimization tools to two common tuning scenarios. First, we tune simulation inputs to match measurements of a well-characterized experiment at the National Ignition Facility. This type of tuning is commonly performed to compensate for the use of simplified simulation settings (e.g. reduced resolution) or to account for missing physics in the simulations. Second, we search for an ICF simulation design that has a particular radiation drive profile. These optimizations replicate the kinds of tuning researchers routinely perform, but do so with significantly reduced manual effort. This approach demonstrates a powerful and efficient pathway toward autonomous, high-fidelity design optimization for future ICF experiments.

Bayesian optimization↗
DOE OSTI2024

Critical mineral substitutions in IN617: A combined computational and experimental approach to performance evaluation and feasibility

Addressing the escalating demand for critical minerals (CMs) driven by global climate change initiatives, this study explores compositional modifications to Inconel 617 (IN617) by substituting cobalt (Co) with manganese (Mn) across various atomic percentages. Here, we conducted a computational feasibility study employing Molecular Dynamics (MD) simulations to provide strategic guidance for experimental validation. The simulations analyzed tensile strength and corrosion resistance for five modified compositions (M1 to M5) to identify optimal properties. Tensile tests on cubic simulation cells were performed to generate stress-strain curves, revealing the impact of Co replacement with Mn on tensile strength—a metric correlated with hardness. Oxygen penetration simulations were conducted to evaluate corrosion resistance, indicating that reduced oxygen penetration depth corresponds to enhanced resistance. Promising compositions underwent phase diagram calculations for assessing phase stability. The optimal composition (M1), characterized by high tensile strength and minimal oxygen penetration, was chosen for experimental validation using induction melting and friction stir consolidation techniques. The materials were further characterized using SEM-EDS, XRD, and Vickers hardness testing. Our findings suggest that Mn substitution in IN617 can yield mechanical performance at par with high-Co alloys in energy-critical applications.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Multi-Fidelity Bayesian Optimization with Gaussian Processes for Double Shell Inertial Confinement Fusion Target Design

Reliable, secure access to energy is a major focus for national security efforts. One potential route to such energy is through fusion reactions in inertial confinement fusion (ICF) experiments. Such experiments are carried out at facilities such as the National Ignition Facility (NIF) in Livermore, California, where high powered lasers are used to compress a DT fuel-containing target to the necessary high temperature, high pressure conditions. These experiments are limited in number, which creates a heavy dependence on high fidelity predictive physics simulations and analysis performed “pre shot,” or before the experiment occurs. Many of these simulations in higher dimensions (2D and 3D) are computationally expensive, so finding optimal simulation-based designs presents its own challenges. In this work, we present our multi-fidelity Bayesian optimization with Gaussian processes (GPs) for ICF double shell targets, where a 1D surrogate model is used to help find a 2D surrogate model, enabling us to find optimal targets in the higher fidelity (2D), while saving computational cost.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Accelerating laser ray tracing in high fidelity physics simulations of laser melting using squeeze U-net

Laser melting is a core component of the ongoing industrial revolution, dubbed Industry 4.0, as lasers facilitate fast and precise melting and fusion in advanced manufacturing. There is a strong need to optimize the laser process using simulations. However, this has proven challenging as high fidelity simulations are needed for predictive modeling and this is currently prohibitively expensive even when run on hundreds of processors on high performance computers. The challenge is capturing complex physics of laser material interaction, fluid dynamics, thermal physics and material phase transformations at various length and time scales. To close this technological gap, we modified a squeeze U-net to accelerate the laser ray tracing component of such high fidelity models by ~4x–40x while preserving the core physics principle of conservation of energy with 97% accuracy. This approach enables the accurate modeling of global laser energy absorption as a function of local surface temperatures and complex surface topologies, which govern the reflection directions and energy losses of laser rays upon interacting with the material surface.

Computer science↗
DOE OSTI2026

Design optimization of MAPS-based detectors using a data-driven fast simulation approach

A parametric simulation tool for pixel sensors is presented. A realistic pixel response is simulated purely based on measurement input, without requiring detailed knowledge of the underlying manufacturing process. As such, it provides an efficient alternative to the use of Technology Computer-Aided Design simulations, which typically depend on proprietary process information. Due to its parametric approach, the package is fast and thus particularly useful for larger detector systems and high hit rate environments. This work presents measurements, simulation and its validation for the MALTA2 sensor. It is a small collection electrode monolithic active pixel sensor produced in the Tower 180 nm complementary metal-oxide-semiconductor imaging process. Modifications to the sensor’s periphery, mainly in the hit merger, are studied in order to optimize the performance for tracking and calorimetry. This optimization is of special interest as part of the MALTA3 sensor redesign in the 65 nm Tower Partners Semiconductor Co. process.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Fast Adaptive Neural Control of Resonant Extraction at Fermilab

We present progress on the development of a machine learning (ML) regulation system for third-order resonant extraction of the beam delivered to the Mu2e experiment at Fermilab. We consider classical and ML-based controllers optimized on semi-analytic simulations and provide performance comparisons for several models. Additionally, we discuss the efficiency of each model in training, which has implications for future work on adaptive control. We also discuss progress on developing optimized implementations of ML models for edge-based inference.

Whitbeck, A. [Fermilab] (ORCID:0000000342245164)↗
DOE OSTI2025

Fast Adaptive Neural Control of Resonant Extraction at Fermilab

We present progress on the development of a machine learning (ML) regulation system for third-order resonant extraction of the beam delivered to the Mu2e experiment at Fermilab. We consider classical and ML-based controllers optimized on semi-analytic simulations and provide perfor- mance comparisons for several models. Additionally, we discuss the efficiency of each model in training, which has implications for future work on adaptive control. We also discuss progress on developing optimized implementations of ML models for edge-based inference.

Whitbeck, A. [Fermilab]↗
DOE OSTI2025

HPC for Optimizing Process Parameters to Control Material Evolution in Seamless Induction Hardening of Wind Turbine Main Shaft Bearings

Work proposed in this project focused on understanding the effect of martensitic transformation in the steel on the potential for cracking during seamless induction hardening (SIH) as a function of process conditions to allow the process to optimally scale up. Large-scale, three-dimensional phase-field simulations of martensitic transformation were performed using MEUMAPPS-SS (Microstructure Evolution Using Massively Parallel Phase-field Simulations – Solid State) code developed at Oak Ridge National Laboratory. The simulations were guided by location-specific thermal history generated by experimental measurements of time-temperature history generated at The Timken Company. The simulations were able to capture the morphological evolution of the martensite variants in an Fe-1.0C-1.5Cr steel based on the Nishiyama-Wasserman (NW) orientation relationship. The simulations were also able to quantify the stress-state at the interface between impinging martensite variants. The simulations indicated that the magnitude of the various stress and strain components were dependent on the sizes of the impinging plates with a reduction in these quantities with reduced plate size in agreement with experimental findings. The results obtained from the simulations will be used to guide the optimization of the alloy thermal conditions to eliminate quench cracking during SIH of bearing steels.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

SiC Receiver/Reactor by Additive Manufacturing for Concentrated Solar Thermocatalysis with Thermal Energy Storage (Final Technical Report - Public)

The direct use of solar thermal energy provides opportunities for low-cost heating sources for a variety of applications. Ultra-high temperatures around 1000°C are high value and highly useful for energy-demanding industries. Many materials cannot withstand these conditions. In the area of Sustainable Chemicals, further limitations on material stability exist. Combining state-of-the-art materials with new designs provides a promising pathway for harvesting solar thermal energy and performing high temperature chemical processes. However, conventional manufacturing limits the potential for design flexibility. In this project, Additive Manufacturing was combined with advanced materials and new chemical reactor designs. In addition, 24/7 energy is necessary for chemical processing, and designs for ultra-high temperature thermal storage were devised. Specifically, preliminary design of a novel solar thermal receiver was developed in this project and designed to work with thermocatalytic reactors for producing sustainable chemicals and fuels. An ultra-high temperature particle storage system and heat exchangers were proposed to transport ultra-hot air as thermal fluid for the system. On a broader scale, this system could be used to tap solar thermal energy for a centralized facility with capability of transferring that heat to various segments at a full range of temperatures to 1000°C. The project pushed the temperature boundaries past those in current use, and Additive Manufacturing was envisaged for fabricating the receiver to meet requirements of extreme environments. An extensive analysis of silicon carbide additive manufacturing was performed to compare the thermal and mechanical properties of complex geometries compared to conventional material and those manufactured via other methods. The Additive Manufacturing via Binder-Jet printing was optimized and characterized to provide high quality and reproducible components capable of withstanding the proposed extreme environments. The designs for the concentrating solar thermal cavity with ultra-hot air thermal fluid showed high performance in simulations, attributable to the complex optimized geometries of the 3D printed systems. The bright future of Additive Manufacturing with advanced materials developments should provide more options and even higher quality as the technology further develops. Current costs for Additive Manufacturing of advanced ceramics is relatively low, however post-processing of the materials for extreme environments is currently high. There is little industrial-scale infrastructure for these, but it is growing as niche applications become more mainstream. The results of the project can be translated into similar extreme environments for concentrating solar thermal energy as well as its integration with ultra-hot air thermal fluids. A number of industries that require ultra-high temperatures need to electrify or otherwise decarbonize for climate goals, and this project showed that theoretically there is a pathway to do so with direct concentrated solar thermal power.

10 SYNTHETIC FUELS↗
DOE OSTI2025

Simulations of saturated MHD activity in the HBT-EP tokamak

The NIMROD code is used to perform simulations of MHD activity in the HBT-EP tokamak, including the effect of a resistive wall. Linear simulations are conducted to scan current and pressure profiles to establish self-consistent baseline equilibria that result in MHD instabilities with low error between experimental diagnostics and synthetic equivalents. A family of such equilibria is found with relatively peaked current and pressure profiles. Nonlinear simulations are performed using the optimal equilibrium, which is linearly unstable to a Resistive Wall Mode—stable in the ideal wall limit and with an Alfvénic growth rate in the no-wall limit. Using resistive wall boundary conditions, nonlinear Hall MHD simulations yield a rotating, saturated n=1 mode similar to the type observed experimentally in HBT-EP discharges. An n=1 mode around the q=2 surface mediates a localized axisymmetric perturbation that flattens the plasma current from a linearly unstable state to a 3D, rotating, stable state. During the saturated period, periodic changes in inter-diagnostic phase lag allow for qualitative estimations of effective, macroscopic transport coefficients used in MHD closure models and could be extended to model post-disruption MHD structure rotation after thermal quenches seen in HBT-EP.

Arnold, David A. (ORCID:0009000059535761)↗